“Blind” signal detection generally involves receiving and decoding incoming signals when the signal type is not known to the receiver. Many fields of science deal with this type of signal detection, and various techniques have been developed to identify an incoming signal of unknown type, so that its parameters, such as the modulation type and baud rate, can be known and used to decode the signal.
Several examples of signal recognition techniques are parameter-based algorithms, pattern recognition, algorithms that exploit cyclostationarity characteristics, and neural networks. U.S. Pat. No. 6,690,746, entitled “Signal Recognizer for Communications Signals”, assigned to Southwest Research Institute, discusses a system and method for classifying incoming signals as being one of a variety of signal types. Signal parameters are estimated and signals are demodulated in accordance with the estimated parameters.
A subfield of signal recognition includes methods that attempt to decode (or otherwise use) only signals of a desired type. For example, a signal of interest might be a signal that carries a particular training sequence.